Author: Shravan Singh Thakur
Publisher:
Published: 2011
Total Pages: 83
ISBN-13:
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Significant Thermal Analysis-physical chemical data needs to be acquired by the new analyst whether an entry level chemist or a new function for the experienced pharmaceutical scientist. This teaching tool describes the introductory use of Differential Scanning Calorimetry (DSC), Thermogravimetric Analysis (TGA) and Thermomechanical Analysis (TMA) for characterizing pharmaceuticals. Optimum Experimental conditions for DSC, TGA and TMA will focus on collecting the best results and interpretations. Does the sample contain volatiles? Evaporation creates endothermic peaks, 2% water or solvent can lower the glass transition temperature (Tg) by up to 100°C and affect the crystallization temperature on cooling. The decomposition temperature can be determined by DSC and TGA. Decomposition, not volatilization, can result in 5% weight loss and render no meaningful DSC data. The upper DSC temperature for practical use is based on the decomposition temperature. Identical materials can look totally different based on their storage temperature and time, cooling rate from a temperature above the Tg or above the melting temperature (Tm). TMA determines the dimensional change of a sample with respect to temperature. The heating rate, an essential feature of DSC, TGA and TMA can cause multiple variations in transitions. Thermal history of chemicals can affect the ultimate thermal analysis results. TGA can provide information about bound and unbound (free) water due to evaporation, desorption and dehydration. Calibration of DSC and TGA are vital in establishing the precision and accuracy of these unique methods: You must learn and follow the standard protocol ASTM E968 for the heat of fusion and heat capacity as well as ASTM E967 for the determining the transition or phase temperatures of pharmaceuticals. DSC can determine the Tm, crystallization temperature Tc, Tg and the their heats of transition, e.g., fusion and crystallization. A statistical optimum method was developed based on a great deal of supportive data was collected by varying the DSC, TGA, and TMA variables and fitting the results into an experimental design, a 23 factorial design. This was accomplished by the team at Cleveland State University as well as that reported in the thermal and pharmaceutical literature. Typical variables considered were sample size (e.g., 3 vs 15 mgs), heating rate (e.g., 5 vs 20°C/min), atmosphere (e.g., nitrogen vs. air) and humidity exposure (e.g., 100%, wet vs. 0%, dry).
